This New York Times bestseller discusses the impact of automation on jobs and the economy in the near future. What messages does it have?

Many i-programmer book reviews are concerned with the minutiae of current programming languages or frameworks, this review invites you to step away from the keyboard and consider a future where automation significantly reduces the workforce, and its implications for people and the economy.

Traditionally, automation has impacted low-wage jobs, however, any routine work may be a target in the near future, including many white-collar jobs. This book is aimed at anyone with an interest in work, jobs, economy, and the future.

Below is a chapter-by-chapter exploration of the topics covered.

Chapter 1 The Automation Wave

This chapter opens with a look at robots, as part of a general automation movement. Robots have various advantages including being tireless, needing no pay, taking no holidays, and no troublesome injuries and associated lawsuits.

Martin Ford continues with a look at the impact of automation on manufacturing. Various case studies have shown that implementing robot systems increases productivity whilst decreasing staff numbers. Additionally, some jobs, including IT jobs, are moving overseas (offshoring) due to lower wages, but the overwhelming trend is for more automation and less labour.

He next considers the service sector. Automation has already started with the use of ATMs and self-service checkouts, and is expected to have further significant changes in the near future, potentially impacting millions of low-wage jobs. Examples are provided of expected automation in the fast-food industry. Precedence for this is provided in Japan’s sushi restaurants, where automation is able to significantly reduce costs, and out-compete the competition. Other examples of the impact of automation include the rise of Amazon and Netflix, and the corollary demise of Borders and Blockbusters.

Next, the chapter discusses Cloud robots, where computation is offloaded to the cloud, providing a flexible and elastic supply, together with massive parallel processing to quickly produce results.

Robots and advanced self-service technology is currently being deployed to many areas, this is mostly impacting low-paid job. Most economists will argue that while innovation removes jobs, it also creates other, better jobs. The author argues in the remainder of the book this will no longer be the case, instead many fewer jobs are being created, and automation will impact white-collar jobs in the near future.

This chapter provides an interesting overview of what’s happened with automation, and what is likely to happen in the near future. While supporting information is provided for the assertions, and seems plausible, much of it reads as polemic. Useful graphs are provided, together with references to further information. These traits apply to the whole of the book.

Chapter 2 Is This Time Different?

Historically there has been a link between increasing productivity and rising income, however recently this link has broken down. Most US wages have stagnated or declined in real terms, showing itself in increasing inequality, and a jobless recovery. The chapter discusses various economic trends that support the argument that the impact of automation has been deleterious to jobs and the economy, these trends are:

Stagnant wages

Bear market for labour, bull market for corporations

Declining labour force participation

Less jobs, longer recovery, rising long term unemployment

Rising inequality

Declining incomes and unemployment for recent college graduates

Polarization and part-time jobs

The author acknowledges that other factors could also be responsible for the changes, and these are discussed:

Globalization – cheaper manufacturing/services elsewhere

Financialization – growth of finance as % economic activity

Politics – decline of unions means workers do not get most of productivity gains

The chapter ends with a look at the future, arguing that increasing inequality and wage stagnation or decline is likely to continue, while automation increases. I’m a bit concerned the author has overly concentrated on the last recession (2008) in his discussions, this unusual time may inadvertently skew what we are seeing.

This chapter examines the nature of IT, its acceleration, and its impact on the economy. Moore’s law is examined, stated in terms of exponential growth. Computers are getting dramatically better at performing predictable routine work, and are likely to replace people at many of these tasks – and many jobs have plenty of routine tasks e.g. landing a jet plane, and stock trading.

The chapter looks at the changing impact of technology. Google has a significantly higher market value than General Motors (at its peak, adjusted for inflation), but has a lot less employees. Similarly, although the internet is often toted as a great equalizer, in practice it often follows a winner-takes-all model, meaning it is difficult to make sufficient profit unless you’re in prime position (e.g. eBay).

The author suggests that since much research has been funded in the past by the tax payer, perhaps the public has some claim on the accumulated technical balance - more on this later, in relation to a proposed Basic Income Guarantee.

Chapter 4 White-Collar Jobs at Risk

This chapter looks at how automation is increasingly threatening highly-skilled jobs, held by highly educated workers.

The chapter opens with an interesting sports news report. Even more interesting is the report was generated by software. It’s suggested this software could replace more than 90% of journalist by 2025. Similarly, there is a general purpose narrative engine (Quill) that can generate business reports, and perform analysis, all without human involvement.

The chapter next delves into some important underlying technologies, Big Data (storing and processing huge volumes of data quickly), and Machine Learning (using large amounts of data for training, and then apply to new data, continuously improving itself). Machine Learning is use for recommendations by Amazon and Netflix, and for fraud detection.

Next, the chapter examines recent computing advances, including IBM’s Deep Blue computer beating the world champion Gary Kasparov at chess in 1997, and Deep Blue’s successor Watson beating the Jeopardy! winners in 2011. The technology behind Watson was later moved to the cloud, providing even more severs and parallel computing power, and used to provide a second and/or expert opinion on health matters.

Many companies are moving to cloud processing, providing cheaper resources, together with automatic updates, and elastic supply of resources. This will have a significant impact on jobs.

In the 2000s there’s was increasing demand for IT professionals, for programming, networks, PCs etc. Moving to the cloud means many of the infrastructure roles in particular are redundant. Similarly, offshoring has seen the demise of jobs (especially computer programming), being moved to low-wage countries. Despite this, in many developing countries, many graduated cannot find appropriate work.

Next, the impact of automation on education is touched upon. Specifically, Machine Language algorithms that can mark essays, these have a high match to human marking, but are much faster. These are often resented by the education establishment, so it may take some time before they are implemented. The author notes it is possible to give people more skills and education but, ultimately need an alternative approach, since automation will get these improved-skills jobs too.

The chapter ends by suggesting the first white-collar job losses are likely to be for graduates-level new jobs. This will exacerbate existing problems of graduate under-employment.

Overall, the chapter shows that white-collar jobs, including science and IT jobs, are not protected from the impact of automation. Some economists see massive job losses within 20 years, especially if Artificial Intelligence (AI) succeeds in its promise.

Noticeable by its absence, is any mention of cloud security, a growing concern.